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Towards standardisation of evidence-based clinical care process specifications
Scott McLachlan1, Evangelia Kyrimi2, Kudakwashe Dube3
1Health informatics and Knowledge Engineering Research Group (HiKER), New Zealand; Queen Mary University of London, UK.
This study introduces a taxonomy to clarify clinical care process specifications, improving terminology and data consistency. Standardizing these specifications enhances patient data quality and supports integrated Learning Health Systems.
Area of Science:
- Health Informatics
- Clinical Process Modeling
- Healthcare Standardization
Background:
- Healthcare systems face challenges with inconsistent terminology and descriptions of clinical care process specifications.
- This ambiguity hinders effective communication, data recording, and the integration of advanced health systems.
Purpose of the Study:
- To develop a taxonomic characterization of clinical care process specifications.
- To resolve confusion surrounding the terminology and description of these specifications.
- To provide a framework for consistent and computer-interpretable clinical documentation.
Main Methods:
- Analysis of existing literature on clinical care process specifications.
- Extension of the De Bleser approach for characterization.
- Development of a taxonomy based on purpose, core elements, and interrelationships.
- Evaluation using a case study on Type 2 Diabetes diagnosis and treatment in the UK.
Main Results:
- A novel taxonomy for characterizing clinical care process specifications was developed and presented.
- Each specification type was successfully characterized by its purpose, core elements, and relationships.
- The taxonomy was validated through a case study, demonstrating its practical application.
- The framework effectively distinguishes between previously interchangeable terminologies.
Conclusions:
- The developed taxonomy provides a clear framework for understanding and standardizing clinical care process specifications.
- Standardization ensures consistent, high-quality patient information recording and computer interpretability.
- This approach facilitates the integration of Learning Health Systems and reduces terminological confusion in clinical practice.
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